Enterprise Thought Leadership

How does a global marketing team achieve up to a 92% time reduction in content creation? Maria Liw, Global Head of Marketing at SimCorp, reveals the blueprint that transformed her team from AI curious and AI sceptical to AI advocates. In this episode, Tim Bond explores SimCorp's journey to building AI thinking partners and AI Agents with Claude. Maria shares why hands-on training beats theory, how slowing down initially accelerates results, and the unexpected pull effect created by pilot programme success. Essential listening for leaders ready to move from fragmented experiments to coordinated AI transformation, moving from task execution to task orchestration.Guest bioMaria Liw is Global Head of Marketing at SimCorp, a leader in investment management technology serving financial institutions managing over $40 trillion in assets. With over 30 years in the FinTech industry across buy-side, sell-side and technology roles, Maria previously headed global digital, content and MarTech before taking the marketing helm. She leads a 30-40 person team through SimCorp's AI transformation journey.Timestamps00:00:34 Introduction and Tim's European road trip update00:01:00 Maria's role at SimCorp and company background00:02:52 Marketing organisation structure and regional teams00:06:38 How Maria and Tim met through TechPros.io programme00:08:37 Challenges with Microsoft Copilot for content creation00:09:03 Commissioning the pilot as learning opportunity00:11:12 Survey approach and customised workshop design00:11:44 Hands-on learning using real work projects00:13:43 Initial scepticism about content quality00:14:38 Using AI as strategic sparring partner00:15:55 Pull versus push for second training cohort00:17:37 Results: 92% time reduction and productivity metrics00:20:13 Competitive advantage and talent retention benefits00:21:51 Finding space for strategic thinking00:22:52 "Slowing down to move fast" principle00:25:12 Future vision for cross-team AI collaboration00:27:41 Model context protocol and enterprise integration00:29:23 Advice for marketing leaders starting AI journey00:32:08 AI for strategy development not just productionResources and links• Maria Liw on LinkedIn• Tim Bond on LinkedIn • SimCorp • CogniScale (AI training) • TechPros.io • Upcoming Events and Roundtables• Podcast community on LinkedInRelated episodesConsider these related conversations on AI transformation: • Episode 72: Building AI-first content operations • Episode 68: Change management for enterprise AI adoption • Episode 65: Measuring ROI from AI upskilling programmesCalls to actionFollow Enterprise Thought Leadership on your preferred platform: • Spotify• Apple Podcasts • Leave a rating and review to help others discover the podcastHave questions or topics for future episodes? Email: podcasts@techpros.ioFor teams of six or more: Request your free AI Acceleration Report at cogniscale.com using promo code PODCAST to assess your team's AI augmentation potential.

"Agents are like enthusiastic employees who don't have a conscience and aren't afraid of getting fired." This stark warning from Oren Michels, CEO of Barndoor.ai, captures why enterprises desperately need governance for their AI workforce. With documented cases of ungoverned agents accidentally deleting entire code bases, the stakes couldn't be higher.Drawing from his experience founding Mashery (acquired by Intel), Oren recognised that AI agents face the same governance challenges as APIs did 15 years ago – but with far greater risks. He reveals why Anthropic's MCP protocol lacks built-in security, explains the four critical vectors of agent security, and shares why Moderna's HR department is leading their AI agent strategy. For any organisation deploying AI agents, Oren's insights on treating them as digital employees rather than traditional software could mean the difference between transformation and catastrophe.Guest bioOren Michels is CEO and co-founder of Barndoor.ai, pioneering security and governance for AI agents. Previously, he founded Mashery, an API management company acquired by Intel, where he served as GM of Intel's API Management Group. His experience scaling API governance to hundreds of enterprise customers now informs his approach to securing the next generation of digital workers.Topics covered• Understanding MCP and why agents need different protocols than traditional software• The four vectors of agent security: agent identity, human identity, tool access, and tasks• Why agents are "enthusiastic employees without a conscience"• HR and IT collaboration to manage agents as digital employees• Building platforms showing which humans achieve value from agents• Documented failures: ungoverned agents deleting entire code bases• Moderna's HR-led approach to AI agent deployment• Evolution from internal use to cross-company agentic workflows• Future implications for early career professionalsKey timestamps00:00:00 – Introduction to securing AI agents00:02:13 – Why API management patterns apply to AI agents 00:07:15 – MCP protocol and its security gaps00:12:14 – What Barndoor does00:20:06 – Documented failures and ungoverned agents00:23:39 – Moderna's HR-led approach00:26:09 – HRIS for the agent workforce00:34:43 – Future of work and early career challengesResources mentioned• Oren Michels on LinkedIn – CEO of Barndoor.ai • Tim Bond on LinkedIn – Podcast host • Barndoor.ai – AI agent security platform • Intel – Acquired MasheryListen and subscribeFound this valuable? Subscribe on: Spotify | Apple PodcastsJoin our LinkedIn community for ongoing discussionsQuestions? Email: podcasts@techpros.io Learn more: https://techpros.io/Full transcript available below.

A third of CMOs report little to no AI implementation in their organisations. Chris Daly's verdict? "You're gonna be history." In this episode, the CEO of the Chartered Institute of Marketing shares why marketing professionals must rapidly adapt or risk obsolescence. Drawing from his military background and leadership of this 113-year-old institution, Chris reveals how marketing can finally shed its "pens and t-shirts department" reputation to become the engine of business growth. We explore the critical balance between AI adoption and human creativity, examine WPP's 50% devaluation as a cautionary tale, and discover why some agencies now revise their AI policies every three months just to keep pace.Topics covered• Marketing's evolution from sales offshoot to business growth function.• Why professional standards matter more than ever in the AI era.• Four principles for ethical AI implementation in marketing.• The hidden dangers of shadow AI when employees use personal licences.• How bias in AI systems can damage customer relationships.• WPP's challenges and what they signal for traditional agencies.• Why CIM is considering traditional exams again, as AI can too easily complete assignments.• The Global Professional Marketing Framework with 207 competency aspects.• How treating AI as a colleague rather than a barrier preserves customer connection.• Why continuous learning is the only survival strategy for marketers.Timestamps00:00:34 CIM's 113-year journey from sales to chartered status00:02:44 From military values to marketing leadership00:05:29 Professional qualifications: university to C-suite journey00:14:00 The AI changes in marketing education00:17:35 Four principles for ethical AI: integrity, quality, transparency, awareness00:21:00 Breaking free from the "pens and t-shirts department" perception00:26:00 Five brand risks of generative AI adoption00:29:55 Shadow AI: when employees go rogue with personal licences00:33:41 Global Professional Marketing Framework for organisations00:37:16 WPP's value loss and agency changes00:41:14 One habit every marketer needs: staying currentGuest bioChris Daly is CEO of the Chartered Institute of Marketing, the world's largest professional body for marketing with over 30,000 members globally. A former military officer, Chris brings principles of trust, ethics and professionalism from his service background to marketing leadership. He champions marketing as a business growth function and leads CIM's mission to professionalise an industry navigating AI changes.Resources mentioned• Chartered Institute of Marketing - newly redesigned website with qualifications, training and frameworks• Chris Daly on LinkedIn• Tim Bond on LinkedIn• Gartner CMO research February 2024 study on AI adoption• EU AI Act passed March 2024• WPP investor information context on recent valuation changes• IBM partnership for AI training (via CIM website)• Global Professional Marketing Framework launching November 2024 at World Marketing Forum• CIM's four principles for ethical AI use in marketing• Marketing Cloud, CIM's bridge programme between university and first careerRelated episodes• Episode 68: AI changes in enterprise marketing• Episode 71: Building ethical frameworks for business AI adoptionSubscribe and connectEnjoyed this discussion? Follow Enterprise Thought Leadership on Spotify and Apple Podcasts for weekly conversations with business and technology leaders.Rate and review the podcast to help others find these insights. Join our LinkedIn community at Enterprise Thought Leadership for ongoing discussions.Questions for future episodes? Email podcasts@techpros.ioTranscriptA full transcript of this episode is available below for accessibility and reference.This episode was recorded in July 2024. AI developments and statistics may have evolved since recording.

Tim Bond speaks with Rich Waldron, CEO of Tray.ai, who since 2012 has been building the infrastructure that allows AI agents to truly operate within enterprises. Rich explains the difference between AI's reasoning capabilities (the brain) and its ability to take action across systems (the body), and why this distinction matters for organisations implementing agentic technologies.The conversation explores why 60% of early AI projects fail, the importance of specialised agents over "everything agents", and how companies can avoid common pitfalls. Rich shares insights from over a decade of connecting 800+ applications and databases, revealing what separates successful implementations from costly failures.Key topics covered:• Understanding the body and brain concept in AI agents• Why specialised agents outperform generalised ones• Design principles for avoiding hallucinations• Building cross-functional teams for AI success• The shift from traditional software to constantly evolving agents• The opportunities for young professionals to build our agentic future Timestamps:00:00:00 Introduction to agentic workflows 00:01:49 Rich's journey from university to founding Tray.ai 00:05:38 Early recognition of AI's potential 00:07:48 What is an integration platform as a service (IPaaS)? 00:11:31 The body and brain concept explained 00:14:39 Tools vs knowledge in agent design 00:19:21 Over 800 connectors and growing 00:22:15 Human-in-the-loop considerations 00:25:01 Addressing hallucinations in business processes 00:31:00 Getting started with agentic implementation 00:38:00 Growth strategy and market approach 00:42:47 Competitive advantages and future outlook 00:45:11 Advice for young professionals entering the workforceWant to learn more? Visit Tray.ai's website: https://tray.ai  Connect with Rich Waldron on LinkedIn: https://www.linkedin.com/in/richwaldron/  Connect with Tim Bond: https://www.linkedin.com/in/tngbond/ If you like our podcast, please do follow us and rate each episode. Do you have burning topics or questions you'd like us to explore on the podcast? Email our team at podcasts@techpros.ioFind out more about TechPros.io: https://techpros.io/ Upcoming Events and Roundtables: https://techpros.io/virtual-experiences/ Join our budding podcast community on LinkedIn: https://www.linkedin.com/company/enterprise-thought-leadership/

Bryan Murphy, CEO of Smartling, shares how his company evolved from a software-focused translation provider into an AI-enhanced platform that delivers eight times more content for the same budget. Having joined just before ChatGPT's launch, Bryan led a product overhaul achieving 64% revenue growth whilst quadrupling translator productivity.The conversation explores Smartling's journey from neural machine translation to multi-layered AI workflows that solve quality, fluency, and cultural adaptation challenges. Bryan explains their multi-model approach, automated quality assurance systems, and how they help companies like IHG Hotels, British Airways, and IBM translate content at scale.Bryan also reveals why implementing AI across internal operations proved more challenging than the product changes themselves. He shares specific examples from leading company-wide change, the importance of dedicated resources, and why CEOs must be prepared for their initial AI plans to fail and require iteration.Timestamps:01:58 Bryan's background and eBay Motors experience02:24 Joining Smartling and the ChatGPT moment03:18 Company's tech-forward foundation04:02 From neural machine translation to AI translation07:04 Current product architecture and workflow09:22 Multi-model approach and benchmarking11:28 4× productivity gains for translators13:04 8× content for same budget achievement14:58 Customer case studies and industries served16:35 Internal AI challenges across departments19:05 Sales team doubles productivity20:42 Build vs buy debate and last mile complexity25:47 Customer journey and onboarding process28:22 Action steps for enterprise leadersWant to learn more?Visit Smartling website: https://www.smartling.com/ Connect with Bryan Murphy on LinkedIn: https://www.linkedin.com/in/bryanmurphy2/ Connect with Tim Bond: https://www.linkedin.com/in/tngbond/ Email tim.b@techpros.ioIf you like our podcast, please do follow us and rate each episode. Do you have burning topics or questions you'd like us to explore on the podcast? Email our team at podcasts@techpros.ioFind out more about TechPros.io: https://techpros.io/ Upcoming Events and Roundtables: https://techpros.io/virtual-experiences/ Join our budding podcast community on LinkedIn: https://www.linkedin.com/company/enterprise-thought-leadership/

Software development is experiencing substantial changes as AI tools alter how teams build, test, and deploy applications. Kyle Hauptfleisch, Chief Growth Officer at Daemon, explores how organisations can successfully navigate these changes without losing the human element that makes great software possible.Kyle brings extensive experience across technology publishing, advertising, core banking, and now leads digital change initiatives at a boutique consultancy. He explains why the current discourse around AI in development divides experienced engineers, and shares practical insights from Daemon's AI-first squad approach.The conversation covers:• Why AI should augment rather than replace human decision-making in software development• The essential role of stakeholder engagement in AI adoption projects• How AI can improve the entire software development lifecycle from requirements gathering through to documentation• The motorcycle versus bicycle analogy: why using AI requires changing how you work• Moving from orchestra member to conductor: the shift in engineering roles• Performance metrics that demonstrate real progress: lead time from whiteboard to production• Daemon's AI-first squad methodology and how it works with client teams• Three practical steps technology leaders can take to embrace AI-first engineeringKyle addresses the tension between developers who see AI as creativity-killing automation and those embracing the acceleration it provides. He argues that engineering stops when coding starts - highlighting how AI can handle the production work whilst humans focus on problem-solving and design.Timestamps: 02:23 Kyle's background and journey to Daemon 03:28 What Daemon does as a digital and AI consultancy 04:38 The current state of AI adoption in software development 07:25 Framework for AI adoption: strategy, data, culture, and applications 09:31 Stakeholder engagement challenges and solutions 11:32 AI-first squads: the core proposition and methodology 12:07 Performance metrics and measuring success 13:18 How AI helps across the software development lifecycle 14:19 Medical organisation case study: turning data into information 14:30 AI in coding: solving problems that have been solved before 18:10 Documentation and unexpected use cases like case study generation 20:32 The motorcycle versus bicycle analogy 21:26 Deploying AI-first squads versus changing engineering capability 25:58 Three actions for technology leaders to embrace AI-first engineeringWant to learn more? Visit Daemon's website: ⁠http://dae.mn ⁠Connect with Kyle Hauptfleisch on LinkedIn: ⁠https://www.linkedin.com/in/kyle-hauptfleisch-84ba2357/ ⁠Connect with Tim Bond: ⁠https://www.linkedin.com/in/tngbond/⁠Email ⁠tim.b@techpros.io⁠If you like our podcast, please follow us and rate each episode. Do you have burning topics or questions you'd like us to explore on the podcast? Email our team at ⁠podcasts@techpros.io.⁠Find out more about TechPros.io: ⁠https://techpros.io/⁠Upcoming Events and Roundtables: ⁠https://techpros.io/virtual-experiences/⁠Join our budding podcast community on LinkedIn: ⁠https://www.linkedin.com/company/enterprise-thought-leadership/

Tim Bond explores the substantial shift happening in graduate employment as companies increasingly prioritise "AI natives" over traditional degree holders. This episode examines how the conventional university-to-job pipeline is fracturing and what this means for students, parents, and educators navigating an uncertain future.Using insights from leading experts including Sam Altman from OpenAI, alongside research from McKinsey, the World Economic Forum, Microsoft, and LinkedIn, this episode unpacks the emergence of "AI-first hiring" and its implications for the next generation entering the workforce.Key topics covered:• Why 66% of business leaders won't hire candidates without AI skills• The "chasm challenge" - the dangerous gap between job displacement and job creation• How major consulting firms like McKinsey are reducing their graduate intake• The decline in confidence in higher education • Alternative pathways emerging beyond traditional degrees• Essential skills for succeeding in an AI-augmented workplace• Practical strategies for future-proofing your careerThe episode reveals both concerning realities and also opportunities for those who understand and adapt to these changes. From the rise of apprenticeships at companies like IBM and Microsoft to the growing importance of hybrid skills that combine AI fluency with uniquely human capabilities, this episode provides a roadmap for navigating the changing employment landscape.Timestamps:• 02:09 The emergence of AI-first hiring practices• 04:00 Data on employer preferences for AI skills• 06:00 New job categories and roles being created• 07:00 Understanding the "chasm challenge"• 09:00 Adapting to exponential change• 11:00 The education system's struggle to keep pace• 13:00 Alternative pathways to traditional education• 17:00 Essential skills for the AI-augmented workplace• 20:00 Seven-step roadmap for career future-proofing• 24:00 Final thoughts and call for perspectivesWant to learn more? Listen to the AI Daily Brief - 20 New jobs AI might create - https://open.spotify.com/episode/3IubJxqwd3ZF9KSuHs8mw0Connect with Tim Bond: https://www.linkedin.com/in/tngbond/If you like our podcast, please follow us and rate each episode. Do you have burning topics or questions you'd like us to explore on the podcast? Email our team at podcasts@techpros.ioFind out more about TechPros.io: https://techpros.io/ Upcoming events and roundtables: https://techpros.io/virtual-experiences/ Follow us on LinkedIn: https://www.linkedin.com/company/enterprise-thought-leadership/

Tim Bond tackles the widespread confusion around "AI-first" by examining what this approach actually means versus the fearful narratives dominating headlines. Using Google's NotebookLM to create an engaging dialogue, this episode unpacks Tim's recent article and extensive research to separate fact from fiction.The discussion explores how companies like Duolingo and Klarna created unnecessary panic with poorly communicated ‘AI-first’  strategies, whilst organisations like SimCorp achieved outstanding results through teamwise upskilling. Rather than mass redundancies, AI-first represents a shift in workflow sequence - engaging with AI tools at the start of any task to handle initial research, drafting, and analysis and building AI assistants and consultants to automate parts of workflows.Key topics covered:• The actual definition of AI-first as workflow sequencing, not human replacement• SimCorp's case study showing 600% productivity gains without job losses• Why AI-first functions as "cognitive ergonomics" for modern knowledge work• Research findings from Microsoft, McKinsey, PWC, and World Economic Forum• How entry-level roles are evolving rather than disappearing• The importance of upskilling and employee training programmes• Why early adopters see 122% cashflow increases whilst laggards face 23% lossesTimestamps:02:00 - What AI-first actually means 03:52 - Why workflow sequence matters 05:26 - The cognitive ergonomics analogy 07:02 - SimCorp case study results 09:09 - Economic impact and growth opportunities 11:00 - Entry-level role development 12:24 - Skills development requirements 13:32 - Competitive advantages for early adopters 15:25 - Employee satisfaction at AI-advanced companies 16:21 - Investment priorities for successful implementationWant to learn more? Visit Network Sunday website: https://networksunday.com and cogniscale.info Connect with Tim Bond on LinkedIn: https://www.linkedin.com/in/tngbond/If you like our podcast, please do follow and rate us. Do you have an interestng AI transformation story to tell? Email podcasts@techpros.ioFind out more about TechPros.io: https://techpros.io/ Upcoming Events and Roundtables: https://techpros.io/virtual-experiences/ Join our budding podcast community on LinkedIn: https://www.linkedin.com/company/enterprise-thought-leadership/

Tim Bond examines a disconnect that's currently shaping the sprouts of AI transformation through analysis of two reports that have recently been published. Signal Fire's State of Talent Report reveals entry-level hiring at major tech companies has dropped 50% from pre-pandemic levels, while Ethan Mollick's "Making AI Work" research explains why individual workers achieve three times productivity gains with AI, yet companies see minimal organisational impact.This analysis reveals the emergence of "secret cyborgs" - employees who use AI to change their work but conceal these capabilities from their employers. Meanwhile, the traditional talent pipeline that builds future workforces is showing signs of collapsing, creating what may be one of the most substantial organisational challenges of our time.With help from Anthropic and Google Tim synthesizes the reports and an AI podcast dissects why 40% of workers use AI privately while only 20% adoption rates are officially recorded, the breakdown of traditional career progression models, and the geographic shifts occurring as AI talent clusters in new locations. The episode examines Mollick's three-pillar framework - Leadership, Lab, and Crowd - for capturing productivity gains at scale.Main findings include:• How workers are tripling productivity on specific tasks while organisations capture little or no value• Why entry-level hiring has collapsed across major tech companies and startups• The experience paradox: companies demand experience but provide no pathway to gain it• Geographic talent migration driven by AI opportunities and hybrid work preferences• Strategies for converting secret cyborgs into organisational benefitsTimestamps00:00 Introduction and report overview02:08 Analysis begins: Individual versus organisational AI impact03:26 Individual productivity gains: Danish study and American survey findings04:25 The corporate disconnect: 20% official adoption versus 40% actual usage05:09 Secret cyborg phenomenon: Why workers hide AI capabilities06:20 Organisational design challenges: Systems built for human-only work07:22 Task versus job automation: The £50,000 research report example08:20 Workforce change without permission: Professional adoption rates08:58 Signal Fire data: 50% drop in entry-level hiring across tech09:36 Geographic shifts: Austin, Miami, and AI talent clustering10:19 Leadership challenges: Industrial age thinking versus AI hybrid reality11:41 Talent pipeline crisis: The broken pathway to experience13:33 Long-term compound effects of neglected talent development14:11 Anthropic's retention success: Culture and autonomy as differentiators15:24 Mollick's framework: Leadership, Lab, and Crowd orchestration16:20 Laboratory approach: Beyond research towers to practical scaling17:21 The crowd element: Rational secret cyborgs and sharing incentives18:21 Practical recommendations: Creating transparent AI environments19:38 Concrete actions: Benchmarks, provocations, and rewards20:35 The real challenge: Technology ahead of organisational structures21:29 Conclusion: Building trust and environments for shared AI developmentWant to learn more? Access your complimentary AI Acceleration Report from CogniScale - email Tim Bond at tim.bond@networksunday.comRead Signal Fire's State of Talent Report 2025: https://www.signalfire.com/blog/signalfire-state-of-talent-report-2025 Read Ethan Mollick's "Making AI Work": https://www.oneusefulthing.org/p/making-ai-work-leadership-lab-and?triedRedirect=true Connect with Tim Bond: https://www.linkedin.com/in/tngbond/If you like our podcast, please follow us. Do you have burning topics or questions you'd like us to explore on the podcast? Email our team at podcasts@techpros.io. Find out more about TechPros.io: https://techpros.io/Upcoming Events and Roundtables: https://techpros.io/virtual-experiences/Join our podcast community on LinkedIn: https://www.linkedin.com/company/enterprise-thought-leadership/

Tim Bond speaks with Pierre Kremer from Globant about how modern retail architecture creates unified shopping experiences. Pierre shares his expertise on helping retail clients implement technical architectures that support their business models whilst providing excellent customer experiences.Pierre explains how the retail sector has moved beyond traditional e-commerce into unified commerce, where physical and digital shopping experiences work together. He outlines Globant's retail vision based on five key pillars: convenience, consistency, relevance, empowerment, and flexibility.The conversation covers composable architecture and how retailers are moving from monolithic systems to more adaptable, API-driven approaches that accelerate development cycles. Pierre shares real-world examples of advanced checkout experiences, including the LA Clippers' Intuit Dome arena with facial recognition entry and Uniqlo's RFID-equipped checkout system that eliminates item scanning.They also discuss the ROI challenges of certain retail AI applications, the importance of accurate inventory data between online and physical stores, and how blockchain supports better supply chain traceability and sustainability initiatives.• The progression from e-commerce to unified commerce• Composable vs monolithic architecture approaches• Advanced checkout systems like remote payment processing• AI applications in retail and which ones provide real value• How retailers can reduce technology costs and time-to-value• Future retail trends focused on sustainability and personalisationTimestamps01:41 Introduction to modern retail architecture 03:21 Pierre's background and experience 05:07 Globant's Retail Studio vision 07:23 Composable vs monolithic architecture 10:20 Real-world case studies of advanced checkout experiences 14:11 Connecting online and in-store experiences 17:50 AI applications and challenges in retail 21:34 Critical data handoffs between store and online 23:51 Essential business outcomes from modern retail architecture 25:14 Blockchain applications in retail 28:08 Future retail trends and sustainability 32:27 Advice for new technical leadersWant to learn more?Visit Globant's website: https://www.globant.com/Connect with Pierre Kremer on LinkedIn: https://www.linkedin.com/in/pierrekremerConnect with Tim Bond: https://www.linkedin.com/in/tngbond/If you like our podcast, please do follow us and rate each episode.Do you have burning topics or questions you'd like us to explore on the podcast?Email our team at podcasts@techpros.ioFind out more about TechPros.io: https://techpros.io/Upcoming Events and Roundtables: https://techpros.io/virtual-experiences/Join our budding podcast community on LinkedIn: https://www.linkedin.com/company/enterprise-thought-leadership/